Medication Reconciliation, Competency, Timely and Effective Care, and Hospital Readmissions

Hospital readmissions within 30 days of discharge result in significant multimillion-dollar penalties to thousands of Medicare-eligible hospitals throughout the United States and are indicators of suboptimal patient healthcare leading to less than ideal health outcomes for previously hospitalized patients. The purpose of this correlation study was to examine the relationship between medication reconciliation, nursing workforce competency, timely and effective care, and Medicare-eligible hospital 30-day readmission rates. The sample of 269 hospitals came from the population of Medicare-eligible hospitals throughout the United States. Complexity theory and the general model of readmission were theoretical frameworks grounding this study. Secondary data were from publicly available governmental databases. The reporting of the F statistic resulted in rejection of the null hypothesis in this study, based on evidence of the existence of a significant correlation between the variables. Findings shows a statistically significant relationship between nursing workforce competency, timely and effective care, and Medicare-eligible hospital 30-day readmission rates. Medication reconciliation, as measured in this study, was not a significant predictor of 30-day readmission rates. Implications of this study for positive social change include an understanding of factors related to hospital 30-day readmission rates to help leaders take action to enhance patient care, reduce inpatient care expenses, and decrease Medicare-imposed hospital penalties

Forecasting Dose and Dose Rate from Solar Particle Events Using Locally Weighted Regression Techniques

Continued human exploration of the solar system requires the mitigating of radiation effects from the Sun. Doses from Solar Particle Events (SPE) pose a serious threat to the health of astronauts. A method for forecasting the rate and total severity of such events would give time for the astronauts to take actions to mitigate the effects from an SPE. The danger posed from an SPE depends on dose received and the temporal profile of the event. The temporal profile describes how quickly the dose will arrive (dose rate). Previously deployed methods used neural networks to predict the total dose from the event. Later work added the ability to predict the temporal profiles using the neural network approach. Locally weighted regression (LWR) techniques were then investigated for use in forecasting the total dose from an SPE. That work showed that LWR methods could forecast the total dose from an event. This previous research did not calculate the uncertainty in a forecast. The present research expands the LWR model to forecast dose and temporal profile from an SPE along with the uncertainty in these forecasts. Forecasts made with LWR method are able to make forecasts at a time early in an event with results that can be beneficial to operators and crews. The forecasts in this work are all made at or before five hours after the start of the SPE. For 58 percent of the events tested, the dose-rate profile is within the uncertainty bounds. Restricting the data set to only events less than 145 cGy, 86 percent of the events are within the uncertainty bounds. The uncertainty in the forecasts are large, however the forecasts are being made early enough into an SPE that very little of the dose will have reached the crew. Increasing the number of SPEs in the data set increases the accuracy of the forecasts and reduces the uncertainty in the forecasts

Using Artificial Intelligence Methods to Predict Doses From Large Solar Particle Events in Space

Space exploration presents mankind with an opportunity to investigate and discover the nature of our solar system, galaxy, perhaps even the universe. The accomplishment of space exploration will only be achieved if the multitude of problems inherent in space travel are solved. One such problem is protecting humans from radiation. The astronauts are able to protect themselves by surrounding themselves with a radiation shield. For the radiation shield to be effective, the astronauts must have advanced warning of incoming radiation in order to seek shelter in a timely manner. The parameterization of a time-dose profile from an SPE reveals that a non-linear 3 parameter Wiebull curve fits the data very well. Neural networks excel at predicting non-linear functions and their processing in a time period that is much shorter than traditional algorithms used to solve non-linear relationships. Locally weighted regression (LWR), is able to handle non-linear events by performing linear regression on a region locally to the query. Both methods are able to forecast the maximum potentially absorbed dose from a SPE. Currently only the neural network approach has been expanded to forecast the entire dose-profile of a SPE. The neural networks are able to produce reasonable forecasts within 10 hours from the start of a SPE. The dose received in the first 8 hours is on average around 5 cGy which is not consider a significant health risk to the Astronauts. The error in the prediction of all three wiebull parameters is normally reduced to around 10% within the first 10 hours of an event. The LWR is also able to predict the maximum received dose before a dangerous level of radiation would reach the space craft. On average though, the received dose was around 10 cGy and the time into the event before an accurate forecast is made was longer than when using the neural networks. The neural networks are able to forecast the dose-time profile in a timely fashion. The forecasts occur before a significant dose would have time to reach the astronauts in a near Earth situation. This is accomplished using a sliding time delayed neural network technique. In the same time frame the LWR technique is unable to produce forecasts that are as accurate as the neural networks. However, the forecasts using the LWR are within a reasonable amount of time to provide adequate warning and the method tends to always converge to the correct maximum received dose from a particular SPE

Convection, Thermal Bifurcation, and the Colors of A stars

Broad-band ultraviolet photometry from the TD-1 satellite and low dispersion spectra from the short wavelength camera of IUE have been used to investigate a long-standing proposal of Bohm-Vitense that the normal main sequence A- and early-F stars may divide into two different temperature sequences: (1) a high temperature branch (and plateau) comprised of slowly rotating convective stars, and (2) a low temperature branch populated by rapidly rotating radiative stars. We find no evidence from either dataset to support such a claim, or to confirm the existence of an "A-star gap" in the B-V color range 0.22 <= B-V <= 0.28 due to the sudden onset of convection. We do observe, nonetheless, a large scatter in the 1800--2000 A colors of the A-F stars, which amounts to ~0.65 mags at a given B-V color index. The scatter is not caused by interstellar or circumstellar reddening. A convincing case can also be made against binarity and intrinsic variability due to pulsations of delta Sct origin. We find no correlation with established chromospheric and coronal proxies of convection, and thus no demonstrable link to the possible onset of convection among the A-F stars. The scatter is not instrumental. Approximately 0.4 mags of the scatter is shown to arise from individual differences in surface gravity as well as a moderate spread (factor of ~3) in heavy metal abundance and UV line blanketing. A dispersion of ~0.25 mags remains, which has no clear and obvious explanation. The most likely cause, we believe, is a residual imprecision in our correction for the spread in metal abundances. However, the existing data do not rule out possible contributions from intrinsic stellar variability or from differential UV line blanketing effects owing to a dispersion in microturbulent velocity.Comment: 40 pages, 14 figures, 1 table, AAS LaTex, to appear in The Astrophysical Journa

Sociological and Human Developmental Explanations of Crime: Conflict or Consensus

This paper examines multidisciplinary correlates of delinquency in an attempt to integrate sociological and environmental theories of crime with human developmental and biological explanations of crime. Structural equation models are applied to assess links among biological, psychological, and environmental variables collected prospectively from birth through age 17 on a sample of 800 black children at high risk for learning and behavioral disorders. Results show that for both males and females, aggression and disciplinary problems in school during adolescence are the strongest predictors of repeat offense behavior. Whereas school achievement and family income and stability are also significant predictors of delinquency for males, early physical development is the next strongest predictor for females. Results indicate that some effects on delinquency also vary during different ages. It is suggested that behavioral and learning disorders have both sociological and developmental correlates and that adequate educational resources are necessary to ensure channels of legitimate opportunities for high-risk youths

Linking Auxin with Photosynthetic Rate via Leaf Venation

International audienceLand plants lose vast quantities of water to the atmosphere during photosynthetic gas exchange. In angiosperms, a complex network of veins irrigates the leaf, and it is widely held that the density and placement of these veins determines maximum leaf hydraulic capacity and thus maximum photosynthetic rate. This theory is largely based on interspecific comparisons and has never been tested using vein mutants to examine the specific impact of leaf vein morphology on plant water relations. Here we characterize mutants at the Crispoid (Crd) locus in pea (Pisum sativum), which have altered auxin homeostasis and activity in developing leaves, as well as reduced leaf vein density and aberrant placement of free-ending veinlets. This altered vein phenotype in crd mutant plants results in a significant reduction in leaf hydraulic conductance and leaf gas exchange. We find Crispoid to be a member of the YUCCA family of auxin biosynthetic genes. Our results link auxin biosynthesis with maximum photosynthetic rate through leaf venation and substantiate the theory that an increase in the density of leaf veins coupled with their efficient placement can drive increases in leaf photosynthetic capacity

Herbicide Resistance: Toward an Understanding of Resistance Development and the Impact of Herbicide-Resistant Crops

Development of herbicide-resistant crops has resulted in significant changes to agronomic practices, one of which is the adoption of effective, simple, low-risk, crop-production systems with less dependency on tillage and lower energy requirements. Overall, the changes have had a positive environmental effect by reducing soil erosion, the fuel use for tillage, and the number of herbicides with groundwater advisories as well as a slight reduction in the overall environmental impact quotient of herbicide use. However, herbicides exert a high selection pressure on weed populations, and density and diversity of weed communities change over time in response to herbicides and other control practices imposed on them. Repeated and intensive use of herbicides with the same mechanisms of action (MOA; the mechanism in the plant that the herbicide detrimentally affects so that the plant succumbs to the herbicide; e.g., inhibition of an enzyme that is vital to plant growth or the inability of a plant to metabolize the herbicide before it has done damage) can rapidly select for shifts to tolerant, difficult-to-control weeds and the evolution of herbicide-resistant weeds, especially in the absence of the concurrent use of herbicides with different mechanisms of action or the use of mechanical or cultural practices or both.This is the publisher’s final pdf. The published article is copyrighted by the Weed Science Society of America and can be found at: http://wssajournals.org/loi/wee

Débat avec les responsables scientifiques de l’axe 3

Valérie Carayol : Vous avez dit que « dans la mêlée du direct, nous participons plutôt que nous symbolisons » et que « l’induction se vit au présent ». Hier, avec Wolfgang Settekorn qui nous a parlé de métaphorisations mutuelles avec des exemples visuels et avec Philippe Breton qui nous a parlé d’amalgame, on avait déjà esquissé un rapprochement entre l’induction et les dynamiques spatiales, pas obligatoirement une dynamique temporelle. Est-ce que vous pourriez préciser cette idée du direct, ..

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens